Aim. To assess the impact of the volume of disclosure of information on digital transformation, divided into revenue (revenue generation), cost (operational efficiency improvement), and infrastructure aspects, on the market capitalization of Russian companies from the Moscow Exchange Index. Methods. Based on 216 annual reports of 31 non-financial companies from the Moscow Exchange Index for 2014–2024, using LDA and BERTopic methods, the author’s dictionary of digital transformation terms is constructed. Three classes are identified: revenue generation, operational efficiency improvement and cost management, and development of strategic digital infrastructure. Based on the dictionary, indices of disclosure of information on digital transformation are calculated, i.e., the number of mentions of key terms in annual reports. The impact on market capitalization is estimated using panel regression with fixed effects and robust standard errors. Results. The findings can be used by company management in formulating non-financial information disclosure policy, by investment analysts and portfolio managers in evaluating digital transformation signals in annual reports, and by regulators in developing disclosure standards for digital initiatives. Conclusions. Disclosure of information on digital transformation in the annual reports of Russian companies is perceived by stock market participants as a positive signal; contrary to expectations, the greatest contribution is made by the description of digital transformation aspects related to operational efficiency improvement and cost reduction. The obtained result is consistent with signaling theory and the semi-strong form of the efficient market hypothesis, but shows that investors still do not distinguish between the expected effects of the revenue and cost aspects of digital transformation when making financial decisions.
Aim. To establish the nature, specific features, and problems of the interconnected development of science cities of Russia and urban agglomerations of Russia, as well as ways to enhance the sustainability and balance of such development that extend to the regions “hosting” the science cities and agglomerations. Objectives. To characterize, in the context of historical retrospection, the prerequisites and foundations for the emergence, with the acquisition of official status, and the development of science cities of Russia; to reveal the possibilities of obtaining this status, the typology and problems of science city development, and the specific features of their localization, including in relation to urban agglomerations and urbanized territories with high scientific and technological potential. Methods. Using general scientific methods of inquiry, analysis of a number of scholarly publications and materials from information portals, the authors, drawing on historical, comparativegeographical, typological, statistical, and other approaches and methods, examine the issues of the emergence, current level, and development prospects of science cities of Russia. Their typology is determined, and the problems of their development in interconnection with the development of urban agglomerations are studied. Results. It is established that the level of major cities, metropolitan areas, and the urban agglomerations formed on their basis is most receptive to innovation, and the development of diverse technopark structures together with the existing assets of Soviet-era science cities has determined the emergence and evolution of science cities, with thirteen of them being granted the official status of “science city of Russia”. At the same time, nine of the thirteen science cities of Russia were part of the Moscow agglomeration. Their absence from the St. Petersburg agglomeration appears illogical. Overall, across all science cities of Russia, the population has increased in recent years, but this has not been the case in every one of them. No direct correlation has yet been found between changes in population size and the functional profile of science cities. Some science cities are approaching the stage of transformation into regional technopolises. Conclusions. The study of the interconnectedness of the development of science cities and urban agglomerations should be multidisciplinary in nature. The development of science cities is primarily determined by the formation of “metropolitan” agglomerations and should be aimed at enhancing their sustainable development. This applies to the Moscow agglomeration, which has developed a dense network of science cities of Russia and has the prerequisites for the emergence of regional technopolises. It is necessary to identify and justify the feasibility of creating new satellite cities, including science cities of Russia and regional technopolises, in the St. Petersburg agglomeration and other major agglomerations of Russia.
Aim. To develop a conceptual model of a modular artificial intelligence (AI) system for controlling the expenditures of the Social Fund of Russia (SFR) and to assess its potential effectiveness. Objectives. To analyze the expenditure structure of the SFR and identify the areas that are most critical in terms of misuse risks; to systematize existing practices of AI application in the budget process and to assess their applicability for controlling the expenditures of extrabudgetary funds; to develop an architecture of a modular AI system adapted to the specifics of the SFR’s control procedures; to perform a calculative and analytical assessment of the proposed system’s effectiveness. Methods. The research is based on a systems approach, employing methods of structural-functional analysis, business process modeling, statistical analysis of data from the SFR and the Ministry of Finance of Russia, as well as the expert assessment method to identify the potential effect of AI implementation. The calculation of the labor intensity of control procedures is performed taking into account the standard labor costs established by departmental regulations. Results. A modular AI system architecture is developed, comprising three modules: automatic procurement verification (comparison with balance sheet accounting), risk scoring of social payments (a graph model of applicant connections), and control of medical services (matching the service code with treatment outcomes). The optimal system is based on the principle of combining automated selection of suspicious transactions while preserving the expert role of employees. The probable reduction in misuse of funds is estimated by the authors in the range of 1,2–1,8 % of the SFR budget. The reduction in labor costs for desk audits will allow reallocating freed resources to more complex cases requiring expert assessment. Conclusions. The proposed modular AI system for administering SFR expenditures makes it possible to reduce the time spent on control procedures while preserving the expert role of employees for decision-making in non-standard situations. The results obtained confirm the hypothesis of the expediency of implementing a modular AI-based SFR expenditure control system. Further research may be directed toward pilot testing of the system and the development of a methodology for assessing prevented damage from misuse of budgetary funds.
Aim. To reveal the mediating role of human capital in the impact of demographic structure on economic growth: to establish the direction and magnitude of the mediating effect of educational human capital and health human capital. Objectives. To quantitatively estimate the total effect of the old-age dependency ratio (the ratio of the population aged 65+ to the population aged 15–64) and the child dependency ratio (the ratio of the population aged 0–14 to the population aged 15–64) on real per capita gross regional product (GRP) of Chinese provinces; to isolate from this effect the mediating component transmitted through human capital; to test its statistical significance and measure its share in the total effect; to determine whether educational human capital and health human capital differ in their transmission capacity. Methods . The empirical basis is a balanced panel of 31 Chinese provinces for 2010–2024 (465 observations). The econometric model is based on the per capita GRP equation in the steady state derived from the augmented Solow model (Mankiw — Romer — Weil). To isolate the mediating component, the three-step Baron — Kenny mediation analysis procedure is applied. Educational human capital is measured by the average years of schooling of the population aged six and older; health human capital is measured by the number of health workers per 1,000 population. The article employs two-way fixed effects to control for interprovincial heterogeneity and nationwide shocks; standard errors are calculated using the Driscoll — Kraay method, which is robust to heteroskedasticity, autocorrelation, and cross-panel correlation. Results. Both dependency ratios have a statistically significant negative total effect on per capita GRP: a 1 % increase in the old-age dependency ratio is associated with a decline in per capita GRP of approximately 0,55 %, and a 1 % increase in the child dependency ratio is associated with a decline of 0,29 %. Health human capital exhibits a statistically significant mediating effect: through it, 14,3 % of the total effect of the old-age dependency ratio and 48,6 % of the total effect of the child dependency ratio are transmitted. The mediating effect of educational human capital is not statistically significant: the coefficient of the effect of average years of schooling on per capita GRP does not reach statistical significance. Conclusions. The impact of demographic structure on economic growth is transmitted primarily through health human capital rather than through educational human capital. Robustness checks using lagged dependency ratios confirm this finding. The obtained results suggest the expediency of expanding and reallocating health workers toward maintaining the health of the working-age population.
Aim. To substantiate budget federalism measures aimed at equalizing the provision of merit goods to the population of regions, and to demonstrate the need for a transition from assessing budget capacity to assessing the accessibility of socially significant goods. Objectives. To characterize the forms of federal intergovernmental transfers and their significance for financing merit goods; to analyze the dynamics and functional structure of federal intergovernmental transfers in 2023–2025; to propose a typology of regions by dominant problems in the provision of merit goods to the population and to calculate the average grant dependency index for the identified types. Methods. The research employs methods of systemic, comparative, and structural analysis, a typologization method, and a calculation method. The information base consists of provisions of the budget legislation of Russia, data from the Ministry of Finance of Russia, the Federal Treasury, and scholarly publications devoted to issues of budget federalism, intergovernmental transfers, regional equalization, and social infrastructure. Results. It is established that in 2023–2025, the role of subsidies increased while the share of grants decreased in the structure of federal intergovernmental transfers, reflecting the growing importance of targeted program-project financing of the regions of Russia. A typology of regions of Russia is proposed depending on the dominant problems in the provision of merit goods to the population. The average grant dependency index is calculated taking into account the types of regions. It is shown that the highest formal degree of grant dependency is characteristic of regions with high vulnerability of families with children and regions with low population incomes. Conclusions. Budget federalism in the sphere of merit goods should be assessed not only by the volume of transfers and the level of grant dependency of regions but also by the ability of the instruments employed to reduce territorial disparities in the accessibility of education, healthcare, social protection, culture, and sports. Grants smooth out differences in budget capacity, but specific infrastructure and social deficits require a combination of grants, subsidies, subventions, other transfers, special standards, and intraregional redistribution. The results obtained in the study can be used in the formation of intergovernmental transfers taking into account dominant regional needs.
